Tag Archives: Hayek

The Artificial Boom

Discussion about the current financial crisis has largely devolved into a debate about regulation. What’s more, the general public has been led to believe that economic theory has little to say about the current crisis. In reality, the multitude of work on bubbles, crises, business cycles, and credit crises is far too vast to summarize in a book, let alone one thousand words. What should be clear, however, is that an understanding of the current crisis must begin with a description and explanation of the preceding boom. Along these lines, insight can be obtained from the writings of two prominent economists of the early twentieth century, F.A. Hayek and John Maynard Keynes.

Throughout much of the past decade, the main economic debate in the United States centered on the behavior of real wages. As the economy continued to grow, wages by and large failed to keep up after adjusting for inflation. This data point largely resulted in a partisan debate between those who blamed the recent changes in tax policy and those who blamed rising health care costs (total compensation, after all, was rising even if wages were not). With the onset of the current financial crisis this discussion has faded into the background. Nevertheless it is important to understand the bizarre characteristics of the boom in order to fully understand the current situation and to draw inferences for policy analysis. As alluded to previously, a meaningful explanation of the boom-bust scenario of the past decade can be found by reading the major work of Hayek and Keynes.

For Hayek, policies of price level stabilization are the source of business cycle fluctuations as they advocate having the money supply move in lockstep with real economic growth. Such stabilization policies are consistent with the Federal Reserve policies during the tenure of Alan Greenspan. Thus during the early part of this decade when productivity was growing at a record pace putting downward pressure on prices, Greenspan was attempting to stabilize prices through the lower interest rates facilitated by increases in the money supply.

The explanation of the boom-bust scenario that follows from attempts at price level stabilization is provided most forcefully in Hayek’s Price and Production, a collection of lectures given at the London School of Economics in the early 1930s. According to Hayek, when the government increases the money supply and thereby lowers interest rates, it results in more roundabout methods of production that would previously be unprofitable under higher interest rates. Since this increase in production activity is not the result of private saving, consumers continue to anticipate the same level of expenditures on consumption. The result is a temporary boom as spending on production goods increases and individuals maintain consumption expenditures.

However, boom is not sustainable. The increased competition for resources due to the lower interest rates cause the price of the goods used in the production process to rise and therefore translates to higher prices for consumer goods as well. Consumers therefore have to sacrifice some part of what they used to consume. This is not the result of a voluntary choice, but rather the fact that they can now purchase less consumer goods with their current income. However, when the monetary expansion concludes and the money has made its way to workers through higher incomes, they will be able to resume the previous proportion of consumption by increasing expenditures. This change will force the structure of production to become less roundabout and therefore capital which was sunk into areas that are now unprofitable will result in a loss and the onset of a downturn in the business cycle.

Before discussing the downturn, it is important to discuss the implications that can be drawn from the artificial boom. As one can easily infer from the previous description of the boom, while workers are receiving higher nominal incomes, their real incomes are simultaneously depressed by rising prices. In other words, in the absence of another source of growth, real wages will be stagnant.

This scenario clearly fits with what we saw for the better part of this decade. Alan Greenspan lowered interest rates and left them low for far too long in an attempt to stabilize the price level and prevent an economic downturn in the wake of a mild recession. The result was an artificial boom in which real wages were largely stagnant and growth was narrowly concentrated.

Even though Hayek’s theory provides an ample explanation of the artificial boom, it does not imply that a financial crisis akin to what we are experiencing will necessarily follow. For an understanding of the financial crisis, we must turn to John Maynard Keynes.

A central theme of Keynes’s General Theory of Employment, Interest, and Money is the role of uncertainty in economic behavior. As the eminent scholar on Keynes, Paul Davidson has repeatedly highlighted the fact that the world in which we live is largely non-ergodic, or incapable of probabilistic prediction. For Keynes, uncertainty was not merely a term for the improbable, rather it was the concept that there are events in which there exists no identifiable or predictable probability distribution of outcome. It is in this sense that securitization and the subsequent financial market collapse can be put into context.

In addition to stimulating demand, the low interest rates created a quest for yield amongst those in the financial industry. The subsequent result was the increase in the utilization of debt securitization. The conversion of illiquid to liquid assets stoked the fire of the housing market as mortgage debt (and later other types of debt as well) could be removed from the balance sheets of these institutions and the influx of the proceeds could be used for further lending. Armed with what many believed to be assets whose risk followed well-behaved probability distributions, securitization spread to other forms of debt such as student loans, credit card debt and to the securitization of the securities themselves. This idea of quantifiable risk similarly led to the misguided use of credit default swaps to insure against losses.

When the housing price bubble burst and foreclosures spread, the realization of the uncertainty (unquantifiable risk) associated with the various form of asset-backed securities, various equity and debt market behavior devolved quickly into that described by Lord Keynes in Chapter 12 of his General Theory. The weight given to prospective yield fell drastically as market participants increasingly applied greater weight to the expectations of their fellow participants. The subsequent result is found in the herd-like behavior that continues to plague the markets.

Additionally, Keynes’s discussion of the liquidity preference and the determination of the market interest rate are of particular note here as well. As Keynes explicitly explained using his theory of the liquidity preference in 1937, the “desire to hold money as a store of wealth is a barometer of the degree of our distrust of our own calculations and conventions concerning the future.” There is scant a time when this statement has been more prescient. Markets have been plummeting precisely because of the growing of such “distrust” as individuals have sought to escape from the uncertainty surrounding debt and equity markets and instead hold a greater proportion of cash. Further, this preference for liquidity, as Keynes detailed, is what determines the interest rate relative to the money supply. Thus as individuals struggle to understand why credit spreads that reflect the risk of associated with lending such as that between the LIBOR and the Overnight Indexed Swap (OIS) continue to widen, one need only look to the theory of interest outlined in the General Theory. Inter-bank lending rates such as the LIBOR remain elevated due to the fact that, for lack of a better phrase, cash remains king. Until confidence is restored, such conditions are likely to persist.

This analysis is by no means the only example of what economic theory has to say about the current financial crisis and the preceding boom. However, this analysis should serve to demonstrate that, looking back on the past six years or so, the artificial boom and subsequent bust in the United States, which is now spreading throughout the world, can be better understood in light of the pioneering work of F.A. Hayek and John Maynard Keynes. Until we begin to take uncertainty seriously and understand the limitations of price level stabilization, no amount of regulation or intervention will prevent such a crisis in the future.

In the Mail

Prices and Production and Other Works by F.A. Hayek

For years, Monetary Theory and the Trade Cycle and Prices and Production have been scarcely available and consequently at a steep cost. However, the Mises Institute has released a hardback volume that includes both texts as well as several essays by Hayek at a very reasonable price.

More on Radical Uncertainty

Gabriel Mihalache has criticized the views of myself and others on radical uncertainty as follows:

Some people wrongly interpreted Caplan’s point as being one about markets, so they jumped at a chance to criticize a set of complete, contingent markets, but a) this is not about markets, but rather about agents; and b) neoclassical economics can be done with incomplete markets or no markets at all!

Contingent claim markets are used in models of representative agents, so I am not sure where this criticism quite fits. The problem that I have with contingent claim markets and the use of representative agents in general equilibrium theory is far too expansive for a blog post. Similarly, I do not want to get bogged down with other elements of GE theory.

First, I would point out that the world is non-ergodic (to use a term of Doug North, Paul Davidson, and others). As the quote from Keynes in my previous post as well as the work of Schumpeter on creative destruction indicates that there is no probability distribution that exists for invention, innovation, etc. Similarly, as Doug North points out, economists treat uncertainty (as defined in the Knightian sense of the word) as though it is a rare case, when in fact, “it has been the underlying condition responsible for the evolving structure of human organization throughout history and pre-history” (Understanding the Process of Economic Change, Douglass C. North, p. 14).

Thus, ignoring the misuse of uncertainty in the general equilibrium framework, let’s use the classical example of risk and uncertainty from microeconomics. An actuarially fair insurance premium would be such that:

Premium = p*L

where p is the probability of the event and L is the loss. (We can expand this to include a risk premium, but it would not embolden our analysis). Of course, in reality, there are cases where both p and L are unknown. Suppose, for example, one wanted to purchase insurance against the risk of the price of a given commodity falling over an extended period of time. What is the likely price of that commodity 5 years hence? 3 years? 1 year? 3 months? What is the probability that the price will fall? As Keynes would say, “About these matter there is no scientific basis on which to form any calculable probability…”

I am in no way trying to argue that models or risk and uncertainty should be abandoned. They are clearly useful in cases in which the probabilities and potential losses are explicitly known. However, we would do well to recognize that the world is not ergodic and that always and everywhere modeling it as such is an impediment to our understanding of complex human interaction.

Radical Uncertainty

Bryan Caplan has issued a challenge:

Austrian economists often attack the mainstream for ignoring something they call “radical uncertainty,” “sheer ignorance,” or sometimes “Knightian uncertainty.” A common Austrian slogan is that “Neoclassical economists study only cases where people know that they don’t know; we study cases where people don’t know that they don’t know.”

All of this sounds plausible until you press the Austrian to do one of two things:

1. Explain his point using standard probability language. What probability does “don’t know that you don’t know” correspond to? Zero? But if people really assigned p=0 to an event, than the arrival of counter-evidence should make them think that they are delusional, not than a p=0 event has occured.

2. Give a good concrete example.

Austrians (as well as Post Keynesians), I believe, are correct to criticize neoclassical theory in this manner. Neoclassical theory assumes that there is a market of complete contingent contracts with an assigned probability for each anticipated state. This undoubtedly does not reflect reality as there exist states for which no contract is traded. As Keynes explained in “The General Theory of Employment” in the QJE in 1937:

But at any given time facts and expectations were assumed [by the classical economists] to be given in a definite and calculable form; and risks, of which, though admitted, not much notice was taken, were supposed to be capable of an exact actuarial computation. The calculus of probability, though mention of it was kept in the background, was supposed to be capable of reducing uncertainty to the same calculable status as that of certainty itself.

Actually, however, we have, as a rule, only the vaguest idea of any by the most direct consequences of our acts … Thus the fact that our knowledge of the future is fluctuating, vague and uncertain, renders wealth a peculiarly unsuitable subject for the methods of the classical economic theory.

By uncertain knowledge, let me explain, I do not mean merely to distinguish what is known for certain from what is merely probable … The sense in which I am using the term is that in which the price of copper and the rate of interest twenty years hence, or the obsolescence of a new invention are uncertain. About these matter there is no scientific basis on which to form any calculable probability whatever. [Emphasis added.]

The infamous beauty contest described in the General Theory is also a particularly useful analogy for stock market activity and speculation. Of course Keynes was overly pessimistic, in my view, of our ability to form meaningful expectations. Roger Koppl, for example, bridges the gap between Keynes and reality in Big Players and the Economic Theory of Expectations by discussing the emergence of planning horizons, in which each point in the future grows evermore uncertain and therefore the more distant the period, the more open-ended one’s expectations must become. Nevertheless, Keynes’ views on probability theory and economics is much more grounded in reality than the Arrow-Debreu markets for contingent claims.

Perhaps ironically, Keynes’ views on uncertainty are greatly complemented by the work of F.A. Hayek. Whereas Keynes explicitly laid out a vision of why things go wrong, Hayek countered (although not directly) by explaining how things could go right. Hayek’s work on economics and knowledge (here and here, for example) details how, even in the presence of uncertainty and dispersed knowledge, markets serve coordinate behavior and produce efficient outcomes. Similarly, Hayek’s writing on expectations detail how an individual’s views evolve over time and adjust in response to confirmation (or lack thereof) of expectations. Overall, the market provides signals through prices as well as through the profit and loss mechanism and therefore individuals are able to evaluate their expectations and evolve accordingly. Thus, Keynes provides the outline for the radical uncertainty that individuals face and Hayek explains how individuals are able to overcome and cope with said uncertainty. As I have stated previously, this is a much better description of reality than Arrow-Debreu contingent claims.

As to Bryan’s questions, in assigning probabilities (p = x, for example) for events that people don’t know that they don’t know, it is irrelevant what value x takes on as long as their expectations are proven grossly incorrect ex post or the probability of such an event precludes the existence of a contingent contract for that event. Had one posed a question on September 10, 2001 regarding the probability of a terrorist attack the following day the mean probability would undoubtedly not have been equal to 1 (it would likely have been less than 0.01) and I would venture to guess that it is even unlikely that one would have received a single response of 100%. Similarly, for Tyler Cowen’s example of the arrival of the Spaniards.

Is Hayek to Blame for Liquidationism?

The Austrian business cycle theory is often derided for promoting liquidationist policies in the face of depression and recession. This view is never more prevalent than when discussing the Great Depression. This morning, I had a chance to read a forthcoming article by our friend Lawrence White from the Journal of Money, Credit, and Banking in which he tackles the question as to whether the ABCT was really to blame for the liquidationist views. His conclusion is that it was the adherence to the real bills doctrine within the Federal Reserve, not the ABCT, that were closest to these views.

The paper is excellent and supplies (at least in my mind) ample evidence to counteract the accusations that have so long hindered Hayek and the Austrian theory.